View source: R/markcorr_anin.R
markcorr_anin | R Documentation |
Estimate a sector-mark correlation function for second order reweighted "inhomogeneous" pattern.
markcorr_anin( x, marks, u, epsilon, r, lambda = NULL, lambda_h, f = function(a, b) a * b, r_h, stoyan = 0.15, renormalise = TRUE, bootsize = 1e+05, normaliser = NULL, border = 1, divisor = "d", ... )
x |
pp, list with $x~coordinates $bbox~bounding box |
marks |
if x is not marked (x$marks is empty), use these marks |
u |
unit vector(s) of direction, as row vectors. Default: x and y axis. |
epsilon |
Central half angle for the directed sector/cone (total angle of the rotation cone is 2*epsilon) |
r |
radius vector at which to evaluate |
lambda |
optional vector of intensity estimates at points |
lambda_h |
if lambda missing, use this bandwidth in a kernel estimate of lambda(x) |
f |
test function of the form function(m1, m2) ..., returning a vector of length(m1). default: m1*m2 |
r_h |
smoothing for range dimension, epanechnikov kernel |
stoyan |
If r_h not given, use r_h=stoyan/lambda^(1/dim). Same as 'stoyan' in spatstat's pcf. |
renormalise |
See details. |
bootsize |
bootstrap size for estimating the normaliser if not given. |
normaliser |
normalising constant under independent marking. If NULL, estimated with bootstrap. |
border |
Use translation correction? Default=1, yes. Only for cuboidal windows. |
divisor |
either "d" or "r". Divide by dist(i,j) ("d") instead of r ("r")? |
... |
passed on to e.g. intensity_at_points |
Computes a second order reweighted version of the mark correlation function.
lambda(x) at points can be given, or else it will be estimated using Epanechnikov kernel smoothing. See
If 'renormalise=TRUE', we normalise the lambda estimate so that sum(1/lambda(x))=|W|. This corresponds in spatstat
's Kinhom
to setting 'normpower=2'.
Returns a dataframe.
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